Triple
T19898543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morioka Reimen |
E478215
|
entity |
| Predicate | typicallyEatenIn |
P104841
|
FINISHED |
| Object | summer |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: summer | Statement: [Morioka Reimen, typicallyEatenIn, summer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicallyEatenIn Context triple: [Morioka Reimen, typicallyEatenIn, summer]
-
A.
typicallyEatenAt
Indicates that something is most commonly or customarily eaten during a particular time, event, or context.
-
B.
isEatenIn
Indicates that one entity (typically food) is consumed within the context, location, or occasion specified by another entity.
-
C.
isTypicallyServedIn
Indicates that something (such as a food or drink) is most commonly or customarily presented or contained within a particular type of vessel or container.
-
D.
commonlyConsumedAt
chosen
Indicates that one entity is typically eaten or drunk during, or in association with, a particular time, event, or context.
-
E.
isTypicallyServedFor
Indicates that one item is most commonly or customarily served as a meal or course for the other (e.g., a dish typically served for breakfast, lunch, or dinner).
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6593fbb348190afa7acf45af406ed |
completed | April 20, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69e537ecda248190895c96afb6243823 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:52 p.m.